Assimilação de Dados de Radiância do Sensor AMSU-A no GSI: Visão Geral sobre sua Importância para a Qualidade das Condições Iniciais na PNT do CPTEC. Assimilação de Dados de Radiância do Sensor AMSU-A no GSI/BAM/CPTEC: Descrição e Importância para a PNT

The Gridpoint Statistical Interpolation (GSI) is the data assimilation system used in the Center for Weather Forecasting and Climate Studies (CPTEC) of the National Institute for Space Research (INPE) since 2013 and is currently part of the Brazilian Global Atmospheric Model (BAM), the GLobal Modeling System (SMG). Through the variational approach applied to the SMG, this system allows for the direct assimilation of radiance data, which currently represents the greatest impact for obtaining a better Numerical Weather Forecast (NWP) quality on a large scale. In order to detail the particularities necessary for the assimilation of these data and call attention to its importance for the quality of the products obtained using the SMG, this study highlights the main points of the treatment of radiance data within the GSI and presents results of an experiment using AMSU-A sensor data on board several satellites to describe the spatial and temporal behavior of the assimilated data, in quantitative and qualitative terms. Using the radiance data as a reference, in a comparison of a short-term forecast of the model with the analyses, it is observed that the latter shows a decrease in error indicating the efficiency of the radiance assimilation process, with a positive impact on the assimilation of other databases, such as the GNSS Concealment Radio evaluated here. This impact should contribute to improving the quality of the PNT products generated by CPTEC, which should be evaluated in the continuation of this research.